* Phase 3: PP-Structure table extraction + personnel column mapper
Adds the personnel-table stage of the pipeline. PaddleOCR's PP-Structure
recognizes table regions and emits HTML, which we parse into a 2D cell
grid. A separate column mapper detects the header row, classifies each
column to a canonical PersonnelEntry field via a synonym dictionary,
and walks the data rows.
Variant handling:
- Different satuan use different column orders and header phrasing.
Supported synonyms for each canonical field are listed in
pipeline/extract/personnel.py (Pangkat / NRP / Pangkat-NRP combo /
Nama / Jabatan dalam Dinas / Jabatan dalam Sprint / Keterangan).
- A merged 'PANGKAT NRP' or 'PANGKAT NRP NAMA' cell is split using
the 8-digit NRP regex (with look-arounds so glued forms like
'BRIPKA98050505' work) and the master pangkat lookup.
- Unknown ranks are kept verbatim so the validation layer can flag
them as UNKNOWN_PANGKAT for HITL review.
- Rows without nrp AND nama are dropped (separators / merged cells).
New module pipeline/table.py:
- DetectedTable dataclass (cells + html).
- parse_table_html: tag/entity-tolerant HTML -> 2D grid.
- extract_tables_from_pp_result: filter PP-Structure regions to type=table.
- run_table_extraction: top-level entrypoint with lazy-init singleton
for the heavy PP-Structure engine.
Orchestrator now invokes table extraction (gated by TABLES_ENABLED) on
every preprocessed page and merges the discovered personnel into the
ExtractionResult. Failures are caught and logged so a flaky table
recognizer never blocks header extraction.
Tests: 38 new unit tests covering HTML parsing, region filtering,
header classification, column mapping (split, combined, glued cells),
and end-to-end personnel extraction. Total 108 tests, all green.
PaddleOCR / PP-Structure remain optional - no test imports them.
Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
* Phase 3: fix header misclassification for combined Pangkat/NRP/Nama columns
Devin Review caught two related bugs in personnel column mapping:
1. _classify_header_cell iterated _HEADER_SYNONYMS in insertion order
when falling back to substring matching. The dict listed shorter
keywords first ('pangkat' before 'pangkat / nrp'), so a header like
'Pangkat / NRP / Nama' classified as plain 'pangkat'. map_row then
tried to normalize the whole '"AKP 87010101 Budi Santoso"' cell
as a rank, normalize_pangkat returned None, and the row failed the
nrp-or-nama gate at the bottom of map_row -- silently dropping
every personnel row in tables using this layout.
2. _split_pangkat_nrp_nama existed and was unit-tested but was never
wired up in map_row, so even if classification had worked, the
three-way split would not have run. The module docstring claimed
the split was supported.
Fix:
- Iterate the synonym table sorted by keyword length descending in the
substring-match fallback so the most specific synonym wins.
- Add 'pangkat_nrp_nama' synonym entries for typical separators
(' / ', '/', whitespace, comma).
- Wire 'pangkat_nrp_nama' into map_row using the existing helper.
- Update is_personnel_table so combined headers count as both an id
signal and a name signal.
Tests: 6 new asserts (parametrized), 1 regression test for triple-
combined header end-to-end, 1 dedicated map_row test for the new
column type. 114 tests total, all green.
Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
* Phase 3: handle multi-word Polri ranks in _split_pangkat_nrp_nama
Devin Review caught: token-by-token is_valid_pangkat() check could not
recognize multi-word ranks ('KOMBES POL', 'BRIGJEN POL', 'IRJEN POL',
'KOMJEN POL', 'JENDERAL POL'). For 'KOMBES POL 88123456 John Doe' the
old code returned pangkat=None, nama='KOMBES POL John Doe', and the
validator's UNKNOWN_PANGKAT flag never fired because pangkat was falsy.
New behavior: greedy longest-prefix match. After stripping the NRP we
try the leading 3-token, 2-token, 1-token slice against
normalize_pangkat() and take the longest that maps to a canonical
rank. Tokens after the matched rank become the nama. Unknown ranks
fall through to pangkat=None and the rank text stays in the nama
field, where downstream validation already flags the row.
Tests: 5 new asserts (4 multi-word ranks + 1 unknown-rank fallback),
119 total green.
Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
* Phase 3: don't count pangkat_nrp as a name signal in is_personnel_table
Devin Review caught: a table with header ['No', 'Pangkat / NRP',
'Jabatan'] (no name column) was wrongly classified as a personnel
table because pangkat_nrp was lumped into has_name. Such a table
would produce PersonnelEntry rows with nama=None passing the nrp-or-
nama gate, polluting the personel[] output with id-only fragments.
Split the combined-cell set into combined_id (counts toward has_id)
and combined_name (counts toward has_name). Only pangkat_nrp_nama,
which actually embeds a name, qualifies for has_name. pangkat_nrp
remains an id-only signal.
Tests: 3 new asserts (rejects id-only, accepts pangkat_nrp + separate
nama, accepts pangkat_nrp_nama). 122 total green.
Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
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